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PhD position on the analysis of EEG recordings from epilepsy patients

The nonlinear time series analysis group of the Department of Information and Communication Technologies of the Universitat Pompeu Fabra, Barcelona, Spain offers a PhD position. The research of the group is positioned at the interface between physics, applied mathematics, and neuroscience. The PhD project will be dedicated to the study of electroencephalographic recordings from epilepsy patients. For details on this line of research please see: https://www.upf.edu/web/ntsa/publications-featured.

The student will receive a fellowship during three years, which can be extended to a fourth year. The contract is renewed yearly provided that sufficient progress has been made. The student will have to teach some seminars in undergraduate physics or math courses at our department. The candidate will work in our nonlinear time series analysis group, an international team that puts a strong emphasis on well-organized supervision of its junior members and regular research activities such as journal clubs, project meetings, etc.

Starting date (planned): October, 2024

Application deadline: May 1st, 2024

Additional information and application

PhD position in "Integrating Human-Centered Design and Generative AI in Technology-Enhanced Learning: Advancing Learning Analytics for effective educational environments"

The Technology Enhanced Learning field has produced digital tools to assist educational stakeholders (e.g. teachers, students) in the creation of pedagogically-sound learning environments. Learning Analytics (LA) is a field within Technology-Enhanced Learning (TEL) that borrows methods from Artificial Intelligence (AI) and helps understanding and optimizing learning environments based on the analysis of educational data. However, the adoption of TEL solutions suffers from an on-going debate about the need to provide a human centered and trustworthy approach to AI. In TEL this debate focuses on the tension between the potential of designing solutions to achieve a more effective education and its impact on human behavior and wellbeing.

Addressing human factors in the design process and implementation of learning technologies is due. Significant effort is still needed to design solutions according to the factors (and methods) proposed by the Human Computer Interaction (HCI) field while also considering factors from the learning sciences field to support a successful learning experience.

Furthermore, taking into account the evolving landscape of Generative AI tailored for educational purposes, it becomes evident that these innovative tools hold the potential to assist educators in the seamless integration of Universal design for Learning (UDL) within authentic educational settings. AI can significantly reduce the time and effort demanded from teachers by providing specialized knowledge and automating some related tasks. However, the reality is that many educators may lack a comprehensive understanding of these technologies, hindering their effective application. Additionally, these tools have not been explicitly tailored to meet the unique needs of teaching and learning practices.

Addressing this multifaceted problem entails grappling with the complexities of integrating Generative AI into effective Learning Technologies to support educational practices while considering the intricacies and diverse dynamics of classrooms and learners. It necessitates a comprehensive exploration of methods, strategies, and cutting-edge technologies that can harness the vast potential of AI to create learning experiences that are not only inclusive but also adaptable and equitable for all (teachers and students). It is key to understand the needs and problems faced by educators, for this reason applying a human-centered approach is key for understanding how to enhance this context with a digital learning environment. 

This project will advance the state of the art in this domain by researching the mechanisms that can enable educational stakeholders engagement throughout the various phases of the Learning Design process by integrating a Human-centered approach.

Starting date (planned): June, 2024

Application deadline: March 15th, 2024

Additional information and application